Due to more powerful mobile user equipment, such as smart-phones and tablets, and the development of real-time video streaming Internet applications, mobile data traffic is expected to increase almost exponentially within the next decade. These trends pose high-demands on the capacity of future wireless networks and one viable way to meet these demands is by means of denser network deployments. In this context, heterogeneous and small cell networks (HSNs), which are characterized by a large number of access nodes (ANs) with different transmit power levels, frequency resources and radio coverage areas, have been considered in industrial standards, such as the LTE/LTE-Advanced standards of the 3rd Generation Partnership Project (3GPP) standards organisation.
HSN deployments will not only yield higher signal-to-interference-plus-noise ratio (SINR) and average data rates but also potentially reduce the networks' energy consumption since it implies an increase in the number of radio access (RA) resources per unit area at a shorter, on average, distance from the users. The term RA resource may refer to a carrier or a channel which is a piece of continuous spectrum of frequencies of a certain bandwidth provided by an access node for users' transmissions. An RA resource may be implemented by one or more antennas and/or antenna elements belonging to one remote radio head (RRH) and/or access node (AN). Each RA resource may be shared by multiple users and it is expected that the average user rates are even higher if users' devices have the ability to be associated with and simultaneously utilize a multiplicity of RA resources.
In traditional cellular radio systems, mobile users access the network by first searching synchronization signals transmitted by network nodes and measuring the strength of the associated reference signals, and then by transmitting an access request to the network node that provides the strongest received signal. A mobile user already connected to the network, on the other hand, is typically required to monitor the signal strength of multiple network nodes so as to facilitate handover from a serving network node to another network node when the signal strength of the latter becomes better than the signal strength of the former. Either procedure aims at assuring that the mobile user is always associated with/connected to the network node that provides the best signal strength. This, however does not guarantee the best usage of the network resources nor assures the best service to the users.
For instance, assuming a network node n applies an equal share of the available time-frequency radio resources of an RA to the served mobile users, the theoretically achievable average user data rate for a user i over RA resource j, ri,j, can be modelled through the Shannon bound as:
            r              i        ,        j              =                            W          j                          L          j                    ⁢                        log          2                ⁡                  (                      1            +                          SINR                              i                ,                j                                              )                      ,where Wj and Lj are the frequency spectrum bandwidth and the traffic load (expressed as the average number of active users served) of RA resource j, while SINRi,j is the signal to noise plus interference ratio experienced by user i from RA resource j. It is clear from this equation that a RA resource j′ with lower traffic load Lj′<Lj can provide a higher average data throughput despite a lower signal strength, i.e., when SINRi,j′<SINRi,j.
The related art 3GPP LTE-A Rel.-12 system has partially addressed this issue by investigating mechanisms for balancing the traffic load among network nodes. The purpose of load shifting/balancing is to improve the system performance by changing the traffic load distribution over network nodes either to obtain a more evenly distributed traffic load across the network nodes or to concentrate the traffic into fewer network nodes so as to mitigate inter-cell interference. To that end, it was proposed to achieve load balancing/shifting via cell association based on:                The strongest reference signal received power (RSRP) in conjunction with a cell association bias;        The strongest reference signal received quality (RSRQ) in conjunction with a cell association bias or threshold;        Long-term SINR UE measurements in conjunction with a cell association bias;        A function of UE measurements (RSRP, RSRQ, and long-term SINR) and of network-side information, e.g. cell resource utilizations;        RSRQ or SINR UE measurements within shortened measurement interval.        
With regards to load balancing and in the context of heterogeneous networks (HetNets), which typically consist of a macro layer and an underlay small-cell layer, it has been recognized that to increase significantly the capacity of the HetNet, mobile users need to be steered toward more lightly loaded network layers (e.g., pico and femtocells), even if they offer a lower SINR than the macro-cell. To that end, the user to cell association is determined by optimizing a function of the long-term user rates, i.e., by solving a network utility maximization problem over all the SINRs and cell loads. This approach has been further developed to include the powering on and off of cells in the context of multi-RAT ultra-dense networks (UDN). Therein, distributing traffic load among cells leads to the activation of more cells, which in non-uniform and low traffic loads show significant user rate improvements for the users at the cell edges.
Also in the case of more recent user-centric proposals for 5G networks, users are simultaneously associated with one or more antennas and/or antenna elements belonging to one or more remote radio heads (RRH) and/or access nodes (ANs) based on:                Uplink mobility beacons sent by the mobile users (in idle or eco mode i.e., the radio or the user plane are not active, but an ID is assigned and tracked by the network);        CSI beacons sent by the mobile users (in active mode, e.g., active radio operation with context in the network node).        
In this first conventional solution, the antenna elements and the ANs constitute an RA resource which a mobile user is associated with and served by. In other words, different groups of antenna elements associated with one or more ANs may constitute one RA resource.
In a second conventional solution enhanced frequency-domain inter-cell interference coordination (ICIC) can be used in LTE when two component carriers (i.e., frequency spectrum bands) are available at a network node. In order to reduce the inter-cell interference, the utilization/activation of component carriers should be coordinated among network nodes. To this end, the available component carriers are categorized into secondary cells (Scells) and primary cell (Pcell). Then, in a first step inter-cell interference is reduced by selecting a Pcell for different geographical areas, similarly to frequency reuse schemes in cellular systems. In a second step, the secondary Scell is activated at a network node for a specific mobile user when high data throughput is requested. One criterion to add an additional Scell is, for instance, when the RSRQ of the Scell is higher than a certain threshold. LTE releases 10 and 11 have introduced several advanced features to reduce interference between macro-layer and pico-layer, such as enhanced ICIC (eICIC), which is particularly suitable for HetNets.
Load balancing and ICIC mechanisms are used for the long time-scale operations based on average performance values. Average performance values are suitable for adapting to changes of the traffic load, however, they filter out fast channel variations, which are associated with diversity gains. For short time-scales, benefiting from diversity requires dynamic selection of RA resources among a multiplicity of RA resources for the transmission of a user's data.
In a third conventional solution, the dynamic selection and transmission of a user's data via an RA resource is performed by means of different multi-radio transmission diversity (MRTD) schemes. MRTD encompasses coordinated multi-point (CoMP), which allow joint transmissions from multiple ANs. Depending on the MRTD and the ICIC/spectrum usage schemes, short time-scale operations may further imply discontinuous transmission (DTX) for a subset or RAs. An extension of this conventional solution is to provide users with flexible access to radio spectrum bands by increased integration of different carriers and different radio access technologies (RATs). The integration of carriers belonging to the same RAT is performed at PHY-layer by means of carrier aggregation (CA). CA is used to increase the bandwidth, and thereby increase the user rate. In 3GPP LTE-A, each aggregated carrier, which is referred to as a component carrier (CC), can have a bandwidth of 1.4, 3, 5, 10, 15 or 20 MHz and a maximum of five component carriers can be aggregated, hence the maximum aggregated bandwidth is 100 MHz. Various forms of CA exist including intra-band, inter-band, and inter-node CA aiming at improving flexibility to the utilisation of the carriers. Assuming devices that support multiple CCs, multi-CC utilization can be performed in terms of dual connectivity. Dual connectivity utilizes simultaneous connections to both the macro-tier and the pico-tier for the transmission of the user data, either simultaneously or in a time division multiplexing manner (TDM).
In the described conventional solutions, a mobile user assists the network in RA resource association, handover and load balancing procedures by sending uplink beacons or by providing feedback related to the received signal strength from multiple network nodes. This, however, is insufficient to assure that the mobile user is connected or handed over to a network node with the potential to offer the required service.
A drawback of the first conventional solution is that it aims at equalizing the load among network nodes without taking into account how the load could be distributed in relation to the available RA resources at each network node.
A drawback of the second conventional solution is that it is designed for two component carriers and assumes a static allocation of the primary component carrier for network nodes (i.e., the Pcell), thus requiring a careful cell planning at the deployment stage. In practice, more than two component carriers, may be made available at the network nodes and their utilization should not be constrained. An additional drawback of the second prior art is that, in the context of HSN, activating more cells or component carriers results in an undesirable increase of the inter-cell interference and thus in a reduction of the spectral efficiency. Interference mitigation and RA resource coordinated utilisation methods that optimise for both the long time-scale and the short-time scale operations are missing. In addition, the RA resource association criteria used to distribute the users among network nodes only accounts for signal quality measures at the mobile users, which is not per se an indication of the service (e.g., data throughput) that can be offered on average to the mobile user by a network node (e.g., due to the traffic load it is expected to serve). In some cases it would be more beneficial to distribute them among multiple RA resources and benefit potentially from both more time frequency resources and diversity gains. A more integrated method would require that that the traffic demands of the user as well as the RA resource and user density are taken into account.
A drawback of the third conventional solutions is that this solution doesn't per se solve the problem of user association with multiple RA resources. The solution only facilitates simultaneous utilisation of a multiplicity of RA resources assuming that the associated RA resources are known. In particular, in very dense networks where users may have access and served by multiple RA resources, solutions of the third prior art does not address distribution of load and proportional fairness in the long run.